Structured Logging

How each logging library represents log entries — plain text versus structured, machine-parsable data.

Winston

Supports structured JSON output through configurable formatters, though plain, human-readable text formatting is equally common depending on how a project configures it.

Pino

Outputs structured JSON by default as its primary format, with human-readable formatting handled by a separate transform (pino-pretty) layered on top for local development.

Python logging

Produces plain-text log lines by default; structured (JSON) output requires a custom Formatter subclass or a third-party extension, since it isn’t a first-class built-in feature.

Loguru

Produces colorized, human-readable text by default, with structured JSON output available as a configurable option (serialize=True) rather than the default.

Log4j2

Supports structured output (JSON, XML) through configurable layouts, alongside its traditional plain-text pattern layout, chosen per appender.

Logback

Also supports structured output through configurable encoders (including a JSON encoder), alongside its traditional plain-text pattern layout.

Zap

Outputs structured JSON by default in production configurations, with a human-readable console encoder available for local development.

slog

Built around structured key-value logging as its core model, with both a JSON handler and a human-readable text handler shipped in the standard library.

tracing

Built around structured, typed fields attached to spans and events from the ground up, with JSON or human-readable formatting handled by pluggable subscriber implementations.

Serilog

Structured logging is its defining feature — log messages use named property placeholders ("User {UserId} logged in") that produce genuinely structured data, not just formatted strings.

Monolog

Produces plain-text lines by default via its line formatter, with a JSON formatter available and commonly used for shipping logs to structured log aggregation services.